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ortools-clone/ortools/constraint_solver/routing_constraints.cc
Corentin Le Molgat a7f49a2585 backport from main 
* rename swig files .i in .swig
* update constraint_solver and routing
* backport math_opt changes
* move dynamic loading to ortools/third_party_solvers
2025-07-23 23:12:34 +02:00

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// Copyright 2010-2025 Google LLC
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include "ortools/constraint_solver/routing_constraints.h"
#include <algorithm>
#include <cstdint>
#include <functional>
#include <limits>
#include <optional>
#include <string>
#include <utility>
#include <vector>
#include "absl/algorithm/container.h"
#include "absl/container/flat_hash_set.h"
#include "absl/functional/any_invocable.h"
#include "absl/log/check.h"
#include "absl/types/span.h"
#include "ortools/base/strong_vector.h"
#include "ortools/constraint_solver/constraint_solver.h"
#include "ortools/constraint_solver/constraint_solveri.h"
#include "ortools/constraint_solver/routing.h"
#include "ortools/constraint_solver/routing_breaks.h"
#include "ortools/constraint_solver/routing_filter_committables.h"
#include "ortools/constraint_solver/routing_filters.h"
#include "ortools/constraint_solver/routing_lp_scheduling.h"
#include "ortools/constraint_solver/routing_search.h"
#include "ortools/util/saturated_arithmetic.h"
namespace operations_research {
namespace {
// Constraint which ensures that var != values.
class DifferentFromValues : public Constraint {
public:
DifferentFromValues(Solver* solver, IntVar* var, std::vector<int64_t> values)
: Constraint(solver), var_(var), values_(std::move(values)) {}
void Post() override {}
void InitialPropagate() override { var_->RemoveValues(values_); }
std::string DebugString() const override { return "DifferentFromValues"; }
void Accept(ModelVisitor* const visitor) const override {
visitor->BeginVisitConstraint(RoutingModelVisitor::kRemoveValues, this);
visitor->VisitIntegerVariableArrayArgument(ModelVisitor::kVarsArgument,
{var_});
visitor->VisitIntegerArrayArgument(ModelVisitor::kValuesArgument, values_);
visitor->EndVisitConstraint(RoutingModelVisitor::kRemoveValues, this);
}
private:
IntVar* const var_;
const std::vector<int64_t> values_;
};
} // namespace
Constraint* MakeDifferentFromValues(Solver* solver, IntVar* var,
std::vector<int64_t> values) {
return solver->RevAlloc(
new DifferentFromValues(solver, var, std::move(values)));
}
namespace {
// For each vehicle, computes information on the partially fixed start/end
// chains (based on bound NextVar values):
// - For every 'end_node', the last node of a start chain of a vehicle,
// vehicle_index_of_start_chain_end[end_node] contains the corresponding
// vehicle index. Contains -1 for other nodes.
// - For every vehicle 'v', end_chain_starts[v] contains the first node of the
// end chain of that vehicle.
void ComputeVehicleChainStartEndInfo(
const RoutingModel& model, std::vector<int64_t>* end_chain_starts,
std::vector<int>* vehicle_index_of_start_chain_end) {
vehicle_index_of_start_chain_end->resize(model.Size() + model.vehicles(), -1);
for (int vehicle = 0; vehicle < model.vehicles(); ++vehicle) {
int64_t node = model.Start(vehicle);
while (!model.IsEnd(node) && model.NextVar(node)->Bound()) {
node = model.NextVar(node)->Value();
}
vehicle_index_of_start_chain_end->at(node) = vehicle;
}
*end_chain_starts = ComputeVehicleEndChainStarts(model);
}
class ResourceAssignmentConstraint : public Constraint {
public:
ResourceAssignmentConstraint(
const RoutingModel::ResourceGroup* resource_group,
const std::vector<IntVar*>* vehicle_resource_vars, RoutingModel* model)
: Constraint(model->solver()),
model_(*model),
resource_group_(*resource_group),
vehicle_resource_vars_(*vehicle_resource_vars) {
DCHECK_EQ(vehicle_resource_vars_.size(), model_.vehicles());
const std::vector<RoutingDimension*>& dimensions = model_.GetDimensions();
for (int v = 0; v < model_.vehicles(); v++) {
IntVar* const resource_var = vehicle_resource_vars_[v];
model->AddToAssignment(resource_var);
// The resource variable must be fixed by the search.
model->AddVariableTargetToFinalizer(resource_var, -1);
if (!resource_group_.VehicleRequiresAResource(v)) {
continue;
}
for (const RoutingModel::DimensionIndex d :
resource_group_.GetAffectedDimensionIndices()) {
const RoutingDimension* const dim = dimensions[d.value()];
// The vehicle's start/end cumuls must be fixed by the search.
model->AddVariableMinimizedByFinalizer(dim->CumulVar(model_.End(v)));
model->AddVariableMaximizedByFinalizer(dim->CumulVar(model_.Start(v)));
}
}
}
void Post() override {}
void InitialPropagate() override {
if (!AllResourceAssignmentsFeasible()) {
solver()->Fail();
}
SetupResourceConstraints();
}
private:
bool AllResourceAssignmentsFeasible() {
DCHECK(!model_.GetResourceGroups().empty());
std::vector<int64_t> end_chain_starts;
std::vector<int> vehicle_index_of_start_chain_end;
ComputeVehicleChainStartEndInfo(model_, &end_chain_starts,
&vehicle_index_of_start_chain_end);
const auto next = [&model = model_, &end_chain_starts,
&vehicle_index_of_start_chain_end](int64_t node) {
if (model.NextVar(node)->Bound()) return model.NextVar(node)->Value();
const int vehicle = vehicle_index_of_start_chain_end[node];
if (vehicle < 0) {
// The node isn't the last node of a route start chain and is considered
// as unperformed and ignored when evaluating the feasibility of the
// resource assignment.
return node;
}
return end_chain_starts[vehicle];
};
const std::vector<RoutingDimension*>& dimensions = model_.GetDimensions();
for (RoutingModel::DimensionIndex d :
resource_group_.GetAffectedDimensionIndices()) {
if (!ResourceAssignmentFeasibleForDimension(*dimensions[d.value()],
next)) {
return false;
}
}
return true;
}
bool ResourceAssignmentFeasibleForDimension(
const RoutingDimension& dimension,
const std::function<int64_t(int64_t)>& next) {
LocalDimensionCumulOptimizer* const optimizer =
model_.GetMutableLocalCumulLPOptimizer(dimension);
if (optimizer == nullptr) return true;
LocalDimensionCumulOptimizer* const mp_optimizer =
model_.GetMutableLocalCumulMPOptimizer(dimension);
DCHECK_NE(mp_optimizer, nullptr);
const auto transit = [&dimension](int64_t node, int64_t /*next*/) {
// TODO(user): Get rid of this max() by only allowing resources on
// dimensions with positive transits (model.AreVehicleTransitsPositive()).
// TODO(user): The transit lower bounds have not necessarily been
// propagated at this point. Add demons to check the resource assignment
// feasibility after the transit ranges have been propagated.
return std::max<int64_t>(dimension.FixedTransitVar(node)->Min(), 0);
};
using RCIndex = RoutingModel::ResourceClassIndex;
const util_intops::StrongVector<RCIndex, absl::flat_hash_set<int>>
ignored_resources_per_class(resource_group_.GetResourceClassesCount());
std::vector<std::vector<int64_t>> assignment_costs(model_.vehicles());
// TODO(user): Adjust the 'solve_duration_ratio' parameter.
for (int v : resource_group_.GetVehiclesRequiringAResource()) {
if (!ComputeVehicleToResourceClassAssignmentCosts(
v, /*solve_duration_ratio=*/1.0, resource_group_,
ignored_resources_per_class, next, transit,
/*optimize_vehicle_costs*/ false,
model_.GetMutableLocalCumulLPOptimizer(dimension),
model_.GetMutableLocalCumulMPOptimizer(dimension),
&assignment_costs[v], nullptr, nullptr)) {
return false;
}
}
// TODO(user): Replace this call with a more efficient max-flow, instead
// of running the full min-cost flow.
return ComputeBestVehicleToResourceAssignment(
resource_group_.GetVehiclesRequiringAResource(),
resource_group_.GetResourceIndicesPerClass(),
ignored_resources_per_class,
[&assignment_costs](int v) { return &assignment_costs[v]; },
nullptr) >= 0;
}
void SetupResourceConstraints() {
Solver* const s = solver();
// Resources cannot be shared, so assigned resources must all be different
// (note that resource_var == -1 means no resource assigned).
s->AddConstraint(s->MakeAllDifferentExcept(vehicle_resource_vars_, -1));
for (int v = 0; v < model_.vehicles(); v++) {
IntVar* const resource_var = vehicle_resource_vars_[v];
if (!resource_group_.VehicleRequiresAResource(v)) {
resource_var->SetValue(-1);
continue;
}
// vehicle_route_considered_[v] <--> vehicle_res_vars[v] != -1.
s->AddConstraint(
s->MakeEquality(model_.VehicleRouteConsideredVar(v),
s->MakeIsDifferentCstVar(resource_var, -1)));
// Reduce domain of resource_var.
const absl::flat_hash_set<int>& resources_marked_allowed =
resource_group_.GetResourcesMarkedAllowedForVehicle(v);
if (!resources_marked_allowed.empty()) {
std::vector<int> allowed_resources(resources_marked_allowed.begin(),
resources_marked_allowed.end());
allowed_resources.push_back(-1);
s->AddConstraint(s->MakeMemberCt(resource_var, allowed_resources));
}
if (resource_var->Bound()) {
ResourceBound(v);
} else {
Demon* const demon = MakeConstraintDemon1(
s, this, &ResourceAssignmentConstraint::ResourceBound,
"ResourceBound", v);
resource_var->WhenBound(demon);
}
}
}
void ResourceBound(int vehicle) {
const int64_t resource = vehicle_resource_vars_[vehicle]->Value();
if (resource < 0) return;
for (const RoutingModel::DimensionIndex d :
resource_group_.GetAffectedDimensionIndices()) {
const RoutingDimension* const dim = model_.GetDimensions()[d.value()];
const RoutingModel::ResourceGroup::Attributes& attributes =
resource_group_.GetResources()[resource].GetDimensionAttributes(dim);
// resource_start_lb <= cumul[start(vehicle)] <= resource_start_ub
// resource_end_lb <= cumul[end(vehicle)] <= resource_end_ub
dim->CumulVar(model_.Start(vehicle))
->SetRange(attributes.start_domain().Min(),
attributes.start_domain().Max());
dim->CumulVar(model_.End(vehicle))
->SetRange(attributes.end_domain().Min(),
attributes.end_domain().Max());
}
}
const RoutingModel& model_;
const RoutingModel::ResourceGroup& resource_group_;
const std::vector<IntVar*>& vehicle_resource_vars_;
};
} // namespace
Constraint* MakeResourceConstraint(
const RoutingModel::ResourceGroup* resource_group,
const std::vector<IntVar*>* vehicle_resource_vars, RoutingModel* model) {
return model->solver()->RevAlloc(new ResourceAssignmentConstraint(
resource_group, vehicle_resource_vars, model));
}
namespace {
class PathSpansAndTotalSlacks : public Constraint {
public:
PathSpansAndTotalSlacks(const RoutingModel* model,
const RoutingDimension* dimension,
std::vector<IntVar*> spans,
std::vector<IntVar*> total_slacks)
: Constraint(model->solver()),
model_(model),
dimension_(dimension),
spans_(std::move(spans)),
total_slacks_(std::move(total_slacks)) {
CHECK_EQ(spans_.size(), model_->vehicles());
CHECK_EQ(total_slacks_.size(), model_->vehicles());
vehicle_demons_.resize(model_->vehicles());
}
std::string DebugString() const override { return "PathSpansAndTotalSlacks"; }
void Post() override {
const int num_nodes = model_->VehicleVars().size();
const int num_transits = model_->Nexts().size();
for (int node = 0; node < num_nodes; ++node) {
auto* demon = MakeConstraintDemon1(
model_->solver(), this, &PathSpansAndTotalSlacks::PropagateNode,
"PathSpansAndTotalSlacks::PropagateNode", node);
dimension_->CumulVar(node)->WhenRange(demon);
model_->VehicleVar(node)->WhenBound(demon);
if (node < num_transits) {
dimension_->TransitVar(node)->WhenRange(demon);
dimension_->FixedTransitVar(node)->WhenBound(demon);
model_->NextVar(node)->WhenBound(demon);
}
}
for (int vehicle = 0; vehicle < spans_.size(); ++vehicle) {
if (!spans_[vehicle] && !total_slacks_[vehicle]) continue;
auto* demon = MakeDelayedConstraintDemon1(
solver(), this, &PathSpansAndTotalSlacks::PropagateVehicle,
"PathSpansAndTotalSlacks::PropagateVehicle", vehicle);
vehicle_demons_[vehicle] = demon;
if (spans_[vehicle]) spans_[vehicle]->WhenRange(demon);
if (total_slacks_[vehicle]) total_slacks_[vehicle]->WhenRange(demon);
if (dimension_->HasBreakConstraints()) {
for (IntervalVar* b : dimension_->GetBreakIntervalsOfVehicle(vehicle)) {
b->WhenAnything(demon);
}
}
}
}
// Call propagator on all vehicles.
void InitialPropagate() override {
for (int vehicle = 0; vehicle < spans_.size(); ++vehicle) {
if (!spans_[vehicle] && !total_slacks_[vehicle]) continue;
PropagateVehicle(vehicle);
}
}
private:
// Called when a path/dimension variables of the node changes,
// this delays propagator calls until path variables (Next and VehicleVar)
// are instantiated, which saves fruitless and multiple identical calls.
void PropagateNode(int node) {
if (!model_->VehicleVar(node)->Bound()) return;
const int vehicle = model_->VehicleVar(node)->Min();
if (vehicle < 0 || vehicle_demons_[vehicle] == nullptr) return;
EnqueueDelayedDemon(vehicle_demons_[vehicle]);
}
// In order to make reasoning on span and total_slack of a vehicle uniform,
// we rely on the fact that span == sum_fixed_transits + total_slack
// to present both span and total_slack in terms of span and fixed transit.
// This allows to use the same code whether there actually are variables
// for span and total_slack or not.
int64_t SpanMin(int vehicle, int64_t sum_fixed_transits) {
DCHECK_GE(sum_fixed_transits, 0);
const int64_t span_min = spans_[vehicle]
? spans_[vehicle]->Min()
: std::numeric_limits<int64_t>::max();
const int64_t total_slack_min = total_slacks_[vehicle]
? total_slacks_[vehicle]->Min()
: std::numeric_limits<int64_t>::max();
return std::min(span_min, CapAdd(total_slack_min, sum_fixed_transits));
}
int64_t SpanMax(int vehicle, int64_t sum_fixed_transits) {
DCHECK_GE(sum_fixed_transits, 0);
const int64_t span_max = spans_[vehicle]
? spans_[vehicle]->Max()
: std::numeric_limits<int64_t>::min();
const int64_t total_slack_max = total_slacks_[vehicle]
? total_slacks_[vehicle]->Max()
: std::numeric_limits<int64_t>::min();
return std::max(span_max, CapAdd(total_slack_max, sum_fixed_transits));
}
void SetSpanMin(int vehicle, int64_t min, int64_t sum_fixed_transits) {
DCHECK_GE(sum_fixed_transits, 0);
if (spans_[vehicle]) {
spans_[vehicle]->SetMin(min);
}
if (total_slacks_[vehicle]) {
total_slacks_[vehicle]->SetMin(CapSub(min, sum_fixed_transits));
}
}
void SetSpanMax(int vehicle, int64_t max, int64_t sum_fixed_transits) {
DCHECK_GE(sum_fixed_transits, 0);
if (spans_[vehicle]) {
spans_[vehicle]->SetMax(max);
}
if (total_slacks_[vehicle]) {
total_slacks_[vehicle]->SetMax(CapSub(max, sum_fixed_transits));
}
}
// Propagates span == sum_fixed_transits + total_slack.
// This should be called at least once during PropagateVehicle().
void SynchronizeSpanAndTotalSlack(int vehicle, int64_t sum_fixed_transits) {
DCHECK_GE(sum_fixed_transits, 0);
IntVar* span = spans_[vehicle];
IntVar* total_slack = total_slacks_[vehicle];
if (!span || !total_slack) return;
span->SetMin(CapAdd(total_slack->Min(), sum_fixed_transits));
span->SetMax(CapAdd(total_slack->Max(), sum_fixed_transits));
total_slack->SetMin(CapSub(span->Min(), sum_fixed_transits));
total_slack->SetMax(CapSub(span->Max(), sum_fixed_transits));
}
void PropagateVehicle(int vehicle) {
DCHECK(spans_[vehicle] || total_slacks_[vehicle]);
const int start = model_->Start(vehicle);
const int end = model_->End(vehicle);
// If transits are positive, the domain of the span variable can be reduced
// to cumul(end) - cumul(start).
if (spans_[vehicle] != nullptr &&
dimension_->AreVehicleTransitsPositive(vehicle)) {
spans_[vehicle]->SetRange(CapSub(dimension_->CumulVar(end)->Min(),
dimension_->CumulVar(start)->Max()),
CapSub(dimension_->CumulVar(end)->Max(),
dimension_->CumulVar(start)->Min()));
}
// Record path, if it is not fixed from start to end, stop here.
// TRICKY: do not put end node yet, we look only at transits in the next
// reasonings, we will append the end when we look at cumuls.
{
path_.clear();
int curr_node = start;
while (!model_->IsEnd(curr_node)) {
const IntVar* next_var = model_->NextVar(curr_node);
if (!next_var->Bound()) return;
path_.push_back(curr_node);
curr_node = next_var->Value();
}
}
// Compute the sum of fixed transits. Fixed transit variables should all be
// fixed, otherwise we wait to get called later when propagation does it.
int64_t sum_fixed_transits = 0;
for (const int node : path_) {
const IntVar* fixed_transit_var = dimension_->FixedTransitVar(node);
if (!fixed_transit_var->Bound()) return;
sum_fixed_transits =
CapAdd(sum_fixed_transits, fixed_transit_var->Value());
}
SynchronizeSpanAndTotalSlack(vehicle, sum_fixed_transits);
// The amount of break time that must occur during the route must be smaller
// than span max - sum_fixed_transits. A break must occur on the route if it
// must be after the route's start and before the route's end.
// Propagate lower bound on span, then filter out values
// that would force more breaks in route than possible.
if (dimension_->HasBreakConstraints() &&
!dimension_->GetBreakIntervalsOfVehicle(vehicle).empty()) {
const int64_t vehicle_start_max = dimension_->CumulVar(start)->Max();
const int64_t vehicle_end_min = dimension_->CumulVar(end)->Min();
// Compute and propagate lower bound.
int64_t min_break_duration = 0;
for (IntervalVar* br : dimension_->GetBreakIntervalsOfVehicle(vehicle)) {
if (!br->MustBePerformed()) continue;
if (vehicle_start_max < br->EndMin() &&
br->StartMax() < vehicle_end_min) {
min_break_duration = CapAdd(min_break_duration, br->DurationMin());
}
}
SetSpanMin(vehicle, CapAdd(min_break_duration, sum_fixed_transits),
sum_fixed_transits);
// If a break that is not inside the route may violate slack_max,
// we can propagate in some cases: when the break must be before or
// must be after the route.
// In the other cases, we cannot deduce a better bound on a CumulVar or
// on a break, so we do nothing.
const int64_t slack_max =
CapSub(SpanMax(vehicle, sum_fixed_transits), sum_fixed_transits);
const int64_t max_additional_slack =
CapSub(slack_max, min_break_duration);
for (IntervalVar* br : dimension_->GetBreakIntervalsOfVehicle(vehicle)) {
if (!br->MustBePerformed()) continue;
// Break must be before end, detect whether it must be before start.
if (vehicle_start_max >= br->EndMin() &&
br->StartMax() < vehicle_end_min) {
if (br->DurationMin() > max_additional_slack) {
// Having the break inside would violate max_additional_slack..
// Thus, it must be outside the route, in this case, before.
br->SetEndMax(vehicle_start_max);
dimension_->CumulVar(start)->SetMin(br->EndMin());
}
}
// Break must be after start, detect whether it must be after end.
// Same reasoning, in the case where the break is after.
if (vehicle_start_max < br->EndMin() &&
br->StartMax() >= vehicle_end_min) {
if (br->DurationMin() > max_additional_slack) {
br->SetStartMin(vehicle_end_min);
dimension_->CumulVar(end)->SetMax(br->StartMax());
}
}
}
}
// Propagate span == cumul(end) - cumul(start).
{
IntVar* start_cumul = dimension_->CumulVar(start);
IntVar* end_cumul = dimension_->CumulVar(end);
const int64_t start_min = start_cumul->Min();
const int64_t start_max = start_cumul->Max();
const int64_t end_min = end_cumul->Min();
const int64_t end_max = end_cumul->Max();
// Propagate from cumuls to span.
const int64_t span_lb = CapSub(end_min, start_max);
SetSpanMin(vehicle, span_lb, sum_fixed_transits);
const int64_t span_ub = CapSub(end_max, start_min);
SetSpanMax(vehicle, span_ub, sum_fixed_transits);
// Propagate from span to cumuls.
const int64_t span_min = SpanMin(vehicle, sum_fixed_transits);
const int64_t span_max = SpanMax(vehicle, sum_fixed_transits);
const int64_t slack_from_lb = CapSub(span_max, span_lb);
const int64_t slack_from_ub = CapSub(span_ub, span_min);
// start >= start_max - (span_max - span_lb).
start_cumul->SetMin(CapSub(start_max, slack_from_lb));
// end <= end_min + (span_max - span_lb).
end_cumul->SetMax(CapAdd(end_min, slack_from_lb));
// // start <= start_min + (span_ub - span_min)
start_cumul->SetMax(CapAdd(start_min, slack_from_ub));
// // end >= end_max - (span_ub - span_min)
end_cumul->SetMin(CapSub(end_max, slack_from_ub));
}
// Propagate sum transits == span.
{
// Propagate from transits to span.
int64_t span_lb = 0;
int64_t span_ub = 0;
for (const int node : path_) {
span_lb = CapAdd(span_lb, dimension_->TransitVar(node)->Min());
span_ub = CapAdd(span_ub, dimension_->TransitVar(node)->Max());
}
SetSpanMin(vehicle, span_lb, sum_fixed_transits);
SetSpanMax(vehicle, span_ub, sum_fixed_transits);
// Propagate from span to transits.
// transit[i] <= transit_i_min + (span_max - span_lb)
// transit[i] >= transit_i_max - (span_ub - span_min)
const int64_t span_min = SpanMin(vehicle, sum_fixed_transits);
const int64_t span_max = SpanMax(vehicle, sum_fixed_transits);
const int64_t slack_from_lb = CapSub(span_max, span_lb);
const int64_t slack_from_ub =
span_ub < std::numeric_limits<int64_t>::max()
? CapSub(span_ub, span_min)
: std::numeric_limits<int64_t>::max();
for (const int node : path_) {
IntVar* transit_var = dimension_->TransitVar(node);
const int64_t transit_i_min = transit_var->Min();
const int64_t transit_i_max = transit_var->Max();
// TRICKY: the first propagation might change transit_var->Max(),
// but we must use the same value of transit_i_max in the computation
// of transit[i]'s lower bound that was used for span_ub.
transit_var->SetMax(CapAdd(transit_i_min, slack_from_lb));
transit_var->SetMin(CapSub(transit_i_max, slack_from_ub));
}
}
// TRICKY: add end node now, we will look at cumuls.
path_.push_back(end);
// A stronger bound: from start min of the route, go to node i+1 with time
// max(cumul[i] + fixed_transit, cumul[i+1].Min()).
// Record arrival time (should be the same as end cumul min).
// Then do the reverse route, going to time
// min(cumul[i+1] - fixed_transit, cumul[i].Max())
// Record final time as departure time.
// Then arrival time - departure time is a valid lower bound of span.
// First reasoning: start - end - start
{
// At each iteration, arrival time is a lower bound of path[i]'s cumul,
// so we opportunistically tighten the variable.
// This helps reduce the amount of inter-constraint propagation.
int64_t arrival_time = dimension_->CumulVar(start)->Min();
for (int i = 1; i < path_.size(); ++i) {
arrival_time =
std::max(CapAdd(arrival_time,
dimension_->FixedTransitVar(path_[i - 1])->Min()),
dimension_->CumulVar(path_[i])->Min());
dimension_->CumulVar(path_[i])->SetMin(arrival_time);
}
// At each iteration, departure_time is the latest time at each the
// vehicle can leave to reach the earliest feasible vehicle end. Thus it
// is not an upper bound of the cumul, we cannot tighten the variable.
int64_t departure_time = arrival_time;
for (int i = path_.size() - 2; i >= 0; --i) {
departure_time =
std::min(CapSub(departure_time,
dimension_->FixedTransitVar(path_[i])->Min()),
dimension_->CumulVar(path_[i])->Max());
}
const int64_t span_lb = CapSub(arrival_time, departure_time);
SetSpanMin(vehicle, span_lb, sum_fixed_transits);
const int64_t maximum_deviation =
CapSub(SpanMax(vehicle, sum_fixed_transits), span_lb);
const int64_t start_lb = CapSub(departure_time, maximum_deviation);
dimension_->CumulVar(start)->SetMin(start_lb);
}
// Second reasoning: end - start - end
{
// At each iteration, use departure time to tighten opportunistically.
int64_t departure_time = dimension_->CumulVar(end)->Max();
for (int i = path_.size() - 2; i >= 0; --i) {
departure_time =
std::min(CapSub(departure_time,
dimension_->FixedTransitVar(path_[i])->Min()),
dimension_->CumulVar(path_[i])->Max());
dimension_->CumulVar(path_[i])->SetMax(departure_time);
}
// Symmetrically to the first reasoning, arrival_time is the earliest
// possible arrival for the latest departure of vehicle start.
// It cannot be used to tighten the successive cumul variables.
int arrival_time = departure_time;
for (int i = 1; i < path_.size(); ++i) {
arrival_time =
std::max(CapAdd(arrival_time,
dimension_->FixedTransitVar(path_[i - 1])->Min()),
dimension_->CumulVar(path_[i])->Min());
}
const int64_t span_lb = CapSub(arrival_time, departure_time);
SetSpanMin(vehicle, span_lb, sum_fixed_transits);
const int64_t maximum_deviation =
CapSub(SpanMax(vehicle, sum_fixed_transits), span_lb);
dimension_->CumulVar(end)->SetMax(
CapAdd(arrival_time, maximum_deviation));
}
}
const RoutingModel* const model_;
const RoutingDimension* const dimension_;
std::vector<IntVar*> spans_;
std::vector<IntVar*> total_slacks_;
std::vector<int> path_;
std::vector<Demon*> vehicle_demons_;
};
} // namespace
Constraint* MakePathSpansAndTotalSlacks(const RoutingDimension* dimension,
std::vector<IntVar*> spans,
std::vector<IntVar*> total_slacks) {
RoutingModel* const model = dimension->model();
CHECK_EQ(model->vehicles(), spans.size());
CHECK_EQ(model->vehicles(), total_slacks.size());
return model->solver()->RevAlloc(new PathSpansAndTotalSlacks(
model, dimension, std::move(spans), std::move(total_slacks)));
}
namespace {
// Very light version of the RangeLessOrEqual constraint (see ./range_cst.cc).
// Only performs initial propagation and then checks the compatibility of the
// variable domains without domain pruning.
// This is useful when to avoid ping-pong effects with costly constraints
// such as the PathCumul constraint.
// This constraint has not been added to the cp library (in range_cst.cc) given
// it only does checking and no propagation (except the initial propagation)
// and is only fit for local search, in particular in the context of vehicle
// routing.
class LightRangeLessOrEqual : public Constraint {
public:
LightRangeLessOrEqual(Solver* s, IntExpr* l, IntExpr* r);
~LightRangeLessOrEqual() override {}
void Post() override;
void InitialPropagate() override;
std::string DebugString() const override;
IntVar* Var() override {
return solver()->MakeIsLessOrEqualVar(left_, right_);
}
// TODO(user): introduce a kLightLessOrEqual tag.
void Accept(ModelVisitor* const visitor) const override {
visitor->BeginVisitConstraint(ModelVisitor::kLessOrEqual, this);
visitor->VisitIntegerExpressionArgument(ModelVisitor::kLeftArgument, left_);
visitor->VisitIntegerExpressionArgument(ModelVisitor::kRightArgument,
right_);
visitor->EndVisitConstraint(ModelVisitor::kLessOrEqual, this);
}
private:
void CheckRange();
IntExpr* const left_;
IntExpr* const right_;
Demon* demon_;
};
LightRangeLessOrEqual::LightRangeLessOrEqual(Solver* const s, IntExpr* const l,
IntExpr* const r)
: Constraint(s), left_(l), right_(r), demon_(nullptr) {}
void LightRangeLessOrEqual::Post() {
demon_ = MakeConstraintDemon0(
solver(), this, &LightRangeLessOrEqual::CheckRange, "CheckRange");
left_->WhenRange(demon_);
right_->WhenRange(demon_);
}
void LightRangeLessOrEqual::InitialPropagate() {
left_->SetMax(right_->Max());
right_->SetMin(left_->Min());
if (left_->Max() <= right_->Min()) {
demon_->inhibit(solver());
}
}
void LightRangeLessOrEqual::CheckRange() {
if (left_->Min() > right_->Max()) {
solver()->Fail();
}
if (left_->Max() <= right_->Min()) {
demon_->inhibit(solver());
}
}
std::string LightRangeLessOrEqual::DebugString() const {
return left_->DebugString() + " < " + right_->DebugString();
}
} // namespace
namespace {
class RouteConstraint : public Constraint {
public:
RouteConstraint(
RoutingModel* model, std::vector<IntVar*> route_cost_vars,
std::function<std::optional<int64_t>(const std::vector<int64_t>&)>
route_evaluator)
: Constraint(model->solver()),
model_(model),
route_cost_vars_(std::move(route_cost_vars)),
route_evaluator_(std::move(route_evaluator)),
starts_(model->Size() + model->vehicles(), -1),
ends_(model->Size() + model->vehicles(), -1) {
const int size = model_->Size() + model_->vehicles();
for (int i = 0; i < size; ++i) {
starts_.SetValue(solver(), i, i);
ends_.SetValue(solver(), i, i);
}
}
~RouteConstraint() override {}
void Post() override {
const std::vector<IntVar*> nexts = model_->Nexts();
for (int i = 0; i < nexts.size(); ++i) {
if (!nexts[i]->Bound()) {
auto* demon = MakeConstraintDemon2(
model_->solver(), this, &RouteConstraint::AddLink,
"RouteConstraint::AddLink", i, nexts[i]);
nexts[i]->WhenBound(demon);
}
}
}
void InitialPropagate() override {
const std::vector<IntVar*> nexts = model_->Nexts();
for (int i = 0; i < nexts.size(); ++i) {
if (nexts[i]->Bound()) {
AddLink(i, nexts[i]);
}
}
}
std::string DebugString() const override { return "RouteConstraint"; }
private:
void AddLink(int index, IntVar* next) {
DCHECK(next->Bound());
const int64_t chain_start = starts_.Value(index);
const int64_t index_next = next->Min();
const int64_t chain_end = ends_.Value(index_next);
starts_.SetValue(solver(), chain_end, chain_start);
ends_.SetValue(solver(), chain_start, chain_end);
if (model_->IsStart(chain_start) && model_->IsEnd(chain_end)) {
CheckRoute(chain_start, chain_end);
}
}
void CheckRoute(int64_t start, int64_t end) {
route_.clear();
for (int64_t node = start; node != end;
node = model_->NextVar(node)->Min()) {
route_.push_back(node);
}
route_.push_back(end);
std::optional<int64_t> cost = route_evaluator_(route_);
if (!cost.has_value()) {
solver()->Fail();
}
route_cost_vars_[model_->VehicleIndex(start)]->SetValue(cost.value());
}
RoutingModel* const model_;
std::vector<IntVar*> route_cost_vars_;
std::function<std::optional<int64_t>(const std::vector<int64_t>&)>
route_evaluator_;
RevArray<int> starts_;
RevArray<int> ends_;
std::vector<int64_t> route_;
};
} // namespace
Constraint* MakeRouteConstraint(
RoutingModel* model, std::vector<IntVar*> route_cost_vars,
std::function<std::optional<int64_t>(const std::vector<int64_t>&)>
route_evaluator) {
return model->solver()->RevAlloc(new RouteConstraint(
model, std::move(route_cost_vars), std::move(route_evaluator)));
}
namespace {
/// GlobalVehicleBreaksConstraint ensures breaks constraints are enforced on
/// all vehicles in the dimension passed to its constructor.
/// It is intended to be used for dimensions representing time.
/// A break constraint ensures break intervals fit on the route of a vehicle.
/// For a given vehicle, it forces break intervals to be disjoint from visit
/// intervals, where visit intervals start at CumulVar(node) and last for
/// node_visit_transit[node]. Moreover, it ensures that there is enough time
/// between two consecutive nodes of a route to do transit and vehicle breaks,
/// i.e. if Next(nodeA) = nodeB, CumulVar(nodeA) = tA and CumulVar(nodeB) = tB,
/// then SlackVar(nodeA) >= sum_{breaks \subseteq [tA, tB)} duration(break).
class GlobalVehicleBreaksConstraint : public Constraint {
public:
explicit GlobalVehicleBreaksConstraint(const RoutingDimension* dimension);
std::string DebugString() const override {
return "GlobalVehicleBreaksConstraint";
}
void Post() override;
void InitialPropagate() override;
private:
void PropagateNode(int node);
void PropagateVehicle(int vehicle);
const RoutingModel* model_;
const RoutingDimension* const dimension_;
std::vector<Demon*> vehicle_demons_;
DimensionValues dimension_values_;
PrePostVisitValues visits_;
std::vector<DimensionValues::Interval> cumul_intervals_;
std::vector<DimensionValues::Interval> slack_intervals_;
BreakPropagator break_propagator_;
};
GlobalVehicleBreaksConstraint::GlobalVehicleBreaksConstraint(
const RoutingDimension* dimension)
: Constraint(dimension->model()->solver()),
model_(dimension->model()),
dimension_(dimension),
dimension_values_(dimension->model()->vehicles(),
dimension->cumuls().size()),
visits_(dimension->model()->vehicles(), dimension->cumuls().size()),
cumul_intervals_(dimension->cumuls().size()),
slack_intervals_(dimension->cumuls().size()),
break_propagator_(dimension->cumuls().size()) {
vehicle_demons_.resize(model_->vehicles());
}
void GlobalVehicleBreaksConstraint::Post() {
for (int vehicle = 0; vehicle < model_->vehicles(); vehicle++) {
if (dimension_->GetBreakIntervalsOfVehicle(vehicle).empty() &&
dimension_->GetBreakDistanceDurationOfVehicle(vehicle).empty()) {
continue;
}
vehicle_demons_[vehicle] = MakeDelayedConstraintDemon1(
solver(), this, &GlobalVehicleBreaksConstraint::PropagateVehicle,
"PropagateVehicle", vehicle);
for (IntervalVar* interval :
dimension_->GetBreakIntervalsOfVehicle(vehicle)) {
interval->WhenAnything(vehicle_demons_[vehicle]);
}
}
const int num_cumuls = dimension_->cumuls().size();
const int num_nexts = model_->Nexts().size();
for (int node = 0; node < num_cumuls; node++) {
Demon* dimension_demon = MakeConstraintDemon1(
solver(), this, &GlobalVehicleBreaksConstraint::PropagateNode,
"PropagateNode", node);
if (node < num_nexts) {
model_->NextVar(node)->WhenBound(dimension_demon);
dimension_->SlackVar(node)->WhenRange(dimension_demon);
}
model_->VehicleVar(node)->WhenBound(dimension_demon);
dimension_->CumulVar(node)->WhenRange(dimension_demon);
}
}
void GlobalVehicleBreaksConstraint::InitialPropagate() {
for (int vehicle = 0; vehicle < model_->vehicles(); vehicle++) {
if (!dimension_->GetBreakIntervalsOfVehicle(vehicle).empty() ||
!dimension_->GetBreakDistanceDurationOfVehicle(vehicle).empty()) {
PropagateVehicle(vehicle);
}
}
}
// This dispatches node events to the right vehicle propagator.
// It also filters out a part of uninteresting events, on which the vehicle
// propagator will not find anything new.
void GlobalVehicleBreaksConstraint::PropagateNode(int node) {
if (!model_->VehicleVar(node)->Bound()) return;
const int vehicle = model_->VehicleVar(node)->Min();
if (vehicle < 0 || vehicle_demons_[vehicle] == nullptr) return;
EnqueueDelayedDemon(vehicle_demons_[vehicle]);
}
// First, perform energy-based reasoning on intervals and cumul variables.
// Then, perform reasoning on slack variables.
void GlobalVehicleBreaksConstraint::PropagateVehicle(int vehicle) {
dimension_values_.Revert();
visits_.Revert();
// Fill dimension_values_ from the path.
// If the path is not a complete start -> end, return.
// This leverages travel caching in FillDimensionValuesFromRoutingDimension().
int node = model_->Start(vehicle);
while (!model_->IsEnd(node)) {
dimension_values_.PushNode(node);
if (model_->NextVar(node)->Bound()) {
node = model_->NextVar(node)->Min();
} else {
return;
}
}
dimension_values_.PushNode(node);
dimension_values_.MakePathFromNewNodes(vehicle);
// Translate CP variables to Intervals, and fill dimension_values_.
const auto& cp_cumuls = dimension_->cumuls();
const auto& cp_slacks = dimension_->slacks();
for (const int node : dimension_values_.Nodes(vehicle)) {
cumul_intervals_[node] = {.min = cp_cumuls[node]->Min(),
.max = cp_cumuls[node]->Max()};
if (dimension_->model()->IsEnd(node)) {
slack_intervals_[node] = {.min = 0, .max = 0};
} else {
slack_intervals_[node] = {.min = cp_slacks[node]->Min(),
.max = cp_slacks[node]->Max()};
}
}
if (!FillDimensionValuesFromRoutingDimension(
vehicle, dimension_->vehicle_capacities()[vehicle],
dimension_->vehicle_span_upper_bounds()[vehicle], cumul_intervals_,
slack_intervals_, dimension_->transit_evaluator(vehicle),
dimension_values_)) {
solver()->Fail();
}
if (!PropagateTransitAndSpan(vehicle, dimension_values_)) {
solver()->Fail();
}
// Extract pre/post visit data.
auto any_invocable = [this](int evaluator_index)
-> std::optional<absl::AnyInvocable<int64_t(int64_t, int64_t) const>> {
const auto& evaluator =
evaluator_index == -1
? nullptr
: dimension_->model()->TransitCallback(evaluator_index);
if (evaluator == nullptr) return std::nullopt;
return evaluator;
};
FillPrePostVisitValues(
vehicle, dimension_values_,
any_invocable(dimension_->GetPreTravelEvaluatorOfVehicle(vehicle)),
any_invocable(dimension_->GetPostTravelEvaluatorOfVehicle(vehicle)),
visits_);
// Copy break data into dimension_values_.
using VehicleBreak = DimensionValues::VehicleBreak;
const std::vector<IntervalVar*>& cp_breaks =
dimension_->GetBreakIntervalsOfVehicle(vehicle);
std::vector<VehicleBreak>& dv_breaks =
dimension_values_.MutableVehicleBreaks(vehicle);
dv_breaks.clear();
for (const IntervalVar* cp_break : cp_breaks) {
if (cp_break->MayBePerformed()) {
dv_breaks.push_back(
{.start = {.min = cp_break->StartMin(), .max = cp_break->StartMax()},
.end = {.min = cp_break->EndMin(), .max = cp_break->EndMax()},
.duration = {.min = cp_break->DurationMin(),
.max = cp_break->DurationMax()},
.is_performed = {.min = cp_break->MustBePerformed(), .max = 1}});
} else {
dv_breaks.push_back({.start = {.min = 0, .max = 0},
.end = {.min = 0, .max = 0},
.duration = {.min = 0, .max = 0},
.is_performed = {.min = 0, .max = 0}});
}
}
// Propagate inside dimension_values_, fail if infeasible.
if (break_propagator_.FastPropagations(vehicle, dimension_values_, visits_) ==
BreakPropagator::kInfeasible) {
solver()->Fail();
}
const auto& interbreaks =
dimension_->GetBreakDistanceDurationOfVehicle(vehicle);
if (break_propagator_.PropagateInterbreak(vehicle, dimension_values_,
interbreaks) ==
BreakPropagator::kInfeasible) {
solver()->Fail();
}
if (!PropagateTransitAndSpan(vehicle, dimension_values_)) {
solver()->Fail();
}
// Copy changes back to CP variables.
using Interval = DimensionValues::Interval;
const int num_nodes = dimension_values_.NumNodes(vehicle);
const absl::Span<const int> nodes = dimension_values_.Nodes(vehicle);
const absl::Span<const Interval> dv_cumuls =
dimension_values_.Cumuls(vehicle);
for (int r = 0; r < num_nodes; ++r) {
const int node = nodes[r];
cp_cumuls[node]->SetRange(dv_cumuls[r].min, dv_cumuls[r].max);
}
const int num_breaks = cp_breaks.size();
for (int b = 0; b < num_breaks; ++b) {
IntervalVar* cp_break = cp_breaks[b];
if (!cp_break->MayBePerformed()) continue;
const VehicleBreak& dv_break = dv_breaks[b];
cp_break->SetStartRange(dv_break.start.min, dv_break.start.max);
cp_break->SetEndRange(dv_break.end.min, dv_break.end.max);
cp_break->SetDurationRange(dv_break.duration.min, dv_break.duration.max);
if (dv_break.is_performed.min == 1) {
cp_break->SetPerformed(true);
} else if (dv_break.is_performed.max == 0) {
cp_break->SetPerformed(false);
}
}
// If everything went fine, we can save dimension state.
// Saving is only done for caching reasons, this allows subsequent calls to
// FillDimensionValuesFromRoutingDimension() to re-use travel evaluations.
dimension_values_.Commit();
visits_.Commit();
}
} // namespace
Constraint* MakeGlobalVehicleBreaksConstraint(
Solver* solver, const RoutingDimension* dimension) {
return solver->RevAlloc(new GlobalVehicleBreaksConstraint(dimension));
}
namespace {
// TODO(user): Make this a real constraint with demons on transit and active
// variables.
class NumActiveVehiclesCapacityConstraint : public Constraint {
public:
NumActiveVehiclesCapacityConstraint(Solver* solver,
std::vector<IntVar*> transit_vars,
std::vector<IntVar*> active_vars,
std::vector<IntVar*> vehicle_active_vars,
std::vector<int64_t> vehicle_capacities,
int max_active_vehicles,
bool enforce_active_vehicles)
: Constraint(solver),
transit_vars_(std::move(transit_vars)),
active_vars_(std::move(active_vars)),
vehicle_active_vars_(std::move(vehicle_active_vars)),
vehicle_capacities_(std::move(vehicle_capacities)),
max_active_vehicles_(
std::min(max_active_vehicles,
static_cast<int>(vehicle_active_vars_.size()))),
enforce_active_vehicles_(enforce_active_vehicles) {
DCHECK_EQ(transit_vars_.size(), active_vars_.size());
DCHECK_EQ(vehicle_capacities_.size(), vehicle_active_vars_.size());
}
std::string DebugString() const override {
return "NumActiveVehiclesCapacityConstraint";
}
void Post() override {
int64_t remaining_demand = 0;
for (int i = 0; i < transit_vars_.size(); ++i) {
if (active_vars_[i]->Min() == 1) {
CapAddTo(transit_vars_[i]->Min(), &remaining_demand);
}
}
sorted_by_capacity_vehicles_.clear();
sorted_by_capacity_vehicles_.reserve(vehicle_capacities_.size());
for (int v = 0; v < vehicle_active_vars_.size(); ++v) {
if (vehicle_active_vars_[v]->Max() == 0) continue;
sorted_by_capacity_vehicles_.push_back(v);
}
const int updated_max_active_vehicles = std::min<int>(
max_active_vehicles_, sorted_by_capacity_vehicles_.size());
absl::c_sort(sorted_by_capacity_vehicles_, [this](int a, int b) {
return vehicle_capacities_[a] > vehicle_capacities_[b];
});
for (int i = 0; i < updated_max_active_vehicles; ++i) {
CapSubFrom(vehicle_capacities_[sorted_by_capacity_vehicles_[i]],
&remaining_demand);
}
if (remaining_demand > 0) solver()->Fail();
// Check vehicles that need to be forced to be active.
if (enforce_active_vehicles_) {
int64_t extended_capacity = 0;
if (updated_max_active_vehicles < sorted_by_capacity_vehicles_.size()) {
extended_capacity = vehicle_capacities_
[sorted_by_capacity_vehicles_[updated_max_active_vehicles]];
}
for (int i = 0; i < updated_max_active_vehicles; ++i) {
const int vehicle = sorted_by_capacity_vehicles_[i];
if (CapAdd(remaining_demand, vehicle_capacities_[vehicle]) >
extended_capacity) {
vehicle_active_vars_[vehicle]->SetValue(1);
} else {
break;
}
}
}
// Check remaining vehicles and make inactive the ones which do not have
// enough capacity.
if (updated_max_active_vehicles > 0 &&
updated_max_active_vehicles - 1 < sorted_by_capacity_vehicles_.size()) {
CapAddTo(
vehicle_capacities_
[sorted_by_capacity_vehicles_[updated_max_active_vehicles - 1]],
&remaining_demand);
}
for (int i = updated_max_active_vehicles;
i < sorted_by_capacity_vehicles_.size(); ++i) {
const int vehicle = sorted_by_capacity_vehicles_[i];
if (vehicle_capacities_[vehicle] < remaining_demand ||
updated_max_active_vehicles == 0) {
vehicle_active_vars_[vehicle]->SetValue(0);
}
}
}
void InitialPropagate() override {}
private:
const std::vector<IntVar*> transit_vars_;
const std::vector<IntVar*> active_vars_;
const std::vector<IntVar*> vehicle_active_vars_;
const std::vector<int64_t> vehicle_capacities_;
const int max_active_vehicles_;
const bool enforce_active_vehicles_;
std::vector<int> sorted_by_capacity_vehicles_;
};
} // namespace
Constraint* MakeNumActiveVehiclesCapacityConstraint(
Solver* solver, std::vector<IntVar*> transit_vars,
std::vector<IntVar*> active_vars, std::vector<IntVar*> vehicle_active_vars,
std::vector<int64_t> vehicle_capacities, int max_active_vehicles,
bool enforce_active_vehicles) {
return solver->RevAlloc(new NumActiveVehiclesCapacityConstraint(
solver, std::move(transit_vars), std::move(active_vars),
std::move(vehicle_active_vars), std::move(vehicle_capacities),
max_active_vehicles, enforce_active_vehicles));
}
} // namespace operations_research
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